The effects we wanted to research are effects of the environment enrichment on our behavior and experience. Rats are a common way to control for many factors which influence us,on a basic level our genetics and the influence of shared and not shared environment. The most common paradigm to research these effects of environment is the enriched environment paradigm (Kempermann (2019)).
Enriched Environment Paradigm:
The Enriched Environment Paradigm is a concept used in psychology and neuroscience to study the effects of a stimulating and complex environment on cognitive development. This paradigm posits that exposure to a rich and diverse environment can enhance learning and brain plasticity. Researchers often use enriched environments in animal studies, providing subjects with toys, social interactions, and novel experiences to measure the impact on cognitive and behavioral outcomes. The Enriched Environment Paradigm has implications for understanding how environmental factors can shape brain development and potentially inform interventions for conditions like Alzheimer’s disease or learning disorders((Nithianantharajah and Hannan 2006) ).
Functional Connectivity
Functional connectivity refers to the statistical association and synchronization of neural activity between different brain regions, indicating the extent to which they work together in performing specific tasks or functions. One of the most research networks is the Default mode network (DMN) which is a connection of multiple regions including the Retrosplenial cortex (RSCx) and the anterior cinculum (ACC). There have been observed aging effects on the FC in the DMN in Rats and Humans ((Zhang et al. 2016)).
CNPase and myelination:
Myelination is the process of insulating nerve fibers in the nervous system with a fatty substance called myelin, which is crucial for the efficient transmission of electrical signals between neurons. Myelin sheaths, formed by specialized cells called oligodendrocytes in the central nervous system. CNPase is an enzyme which is expressed in oligodendrocytes (Baumann and Pham-Dinh (2001)).
“Schematic representation of the different types of glial cells in the central nervous system (CNS) and their interactions, among themselves and with neurons” from Baumann and Pham-Dinh (2001)
Effects of Environment Enrichment on Functional Connectivity:
Research by Hakon et al. (2018) revealed that housing rats in an enriched environment post-stroke led to enhanced regional resting-state functional connectivity compared to those in standard housing, suggesting potential therapeutic implications of environmental stimulation and also demonstrating effects of environment enrichment on functional connectivity.
Anterior Cingular Cortex’s and Retrosplenial Cortex’s connection to spatial navigation:
Both RSCx and and ACC have been shown to be a part of the so called default mode network (Greicius et al. 2009), which is shown to be active during multiple activities such as introspection, but also spatial (van den Heuvel and Hulshoff Pol 2010).
The RSCx has been shown to play a major role in spatial navigation(Mitchell et al. 2018), but specifically in the consolidation of landmarks(Auger, Zeidman, and Maguire 2017).
The ACC has been shown to encode reinforcement and decision making (Kennerley et al. 2006). Besides that it also was demonstrated that it specifically has a part in route selection (Patai and Spiers 2021) and is also sensitive to the spatial location (Mashhoori et al. 2018).
Now, taking all of those findings into account we wanted to focus on the effects environment enrichment has on healthy rats, confirming the most common results in the literature and also looking at the functional connectivity.
We Hypothesize that
A1: Enrichment has an effect on the functional connectivity between the Retrosplenial Cortex and the Anterior Cingular Cortex, thus leading to a difference in the temporal correlation in rs-fMRI
A2: Higher functional connectivity correlates with better behavioral performance regarding spatial navigation
and
B1: Rats with enriched environment show a higher CNPase expression
B2: Rats with enriched environment show a higher performance in the MWM
In our experimental design, we implemented a comprehensive investigative battery to assess the Whistar Rats’ cognitive, physical, and structural changes as they reached the end of their respective lifespans, which could be either 21, 45, or 90 days. For rats whose lifespan ended at 21 and 45 days, the final assessment of their behavior and histology was conducted at those specific time points. This battery included three key components: Firstly, we employed Magnetic Resonance Imaging (MRI) to obtain detailed insights into the rats’ neurobiology. This MRI sequence was consistently carried out at the ages of 21, 45, and 90 days and comprised structural scans, functional MRI (fMRI), and Diffusion Tensor Imaging (DTI) sequences. This allowed us to examine the structural and functional changes in their brains at different stages of their lives. Secondly, we conducted a battery of behavioral tests to assess their cognitive and motor functions. These included experiments such as the Morris Water Maze, Rotarod, and elevated maze tests, which provided valuable insights into their learning, memory, and motor coordination abilities. Lastly, we employed histological analysis, specifically immunostaining, to investigate the histological characteristics of tissue samples from the rats. This helped us understand the cellular and molecular changes that may have occurred during their lifespan.
Graphic of the Study-desing: 4 groups, of which 2 acted as control group. Group size in Standard-cage (SC) was 2-3, where as all the other groups consisted of a group size of 5-6. Big-Cage (BC) Rats where another control group insofar, that they did not enjoy any other sensory stimulation the the SC rats, except the bigger group size. Exerxice-group (EX) had an exercise wheel in their cage which they could use voluntarily. Enriched-Environment-group (EE) had an exercise wheel, toys and platforms, which were rearranged every 3-4 days.
Out test-battery consisted of 3 behavioral Tests. Rotarod performance test(Dunham and Miya 1957), Morris Water Maze navigation task (WM) (Morris 1981) and the Elevated Plus Maze Test (Pellow et al. 1985). All of these Tests assess different behaviors and cognitive states. For this analysis we were mainly interested in spatial learning abilities, thus only looking at the MWM results.
The MWM is an experimental tool used to evaluate the spatial learning abilities of rodents. In this test, animals rely on landmarks in the distance to navigate their way from various starting points along the outer edge of a large pool to find a hidden platform beneath the water’s surface. Spatial learning is measured by observing their performance across multiple attempts, and their reference memory is assessed by determining if they continue to search for the platform location even when it’s not present.
Prior to sectioning, rats were perfused with 4% paraformaldehyde (PFA) to fix the tissue. The fixed tissues were subsequently stored in sucrose before being sliced into 30-micrometer sections.
The tissue sections were then equilibrated to room temperature, rinsed with phosphate-buffered saline (PBS), and blocked with a 5% BSA and 0.1% Triton X-100 solution. Primary antibodies were applied and incubated overnight at 4°C. After PBS rinses, sections were exposed to secondary antibodies in the dark. Following additional PBS rinses, samples were mounted with a suitable medium and covered with a glass coverslip. This protocol enabled specific antigen visualization and data collection with minimal background noise.
For the quantification we used imageJ to determine flourescence intensity. To account for the background noise that was left we used the CTCF (Corrected Total Cell Fluorescence ) formula(El-Sharkawey (2016)), but divided this value by the area of the selected region to account for differences in region size.
\(\frac{(IntegratedDenisty - (AreaOfSelectedCell \times MeanFlourescenceReadingOfBackground))}{AreaOfSelectedCell}\)
A functional magnetic resonance imaging (fMRI) scan was conducted with the following parameters: a repetition time (TR) of 1 second, an echo time (TE) of 20 milliseconds, and a voxel size of 4.6 mm x 4.6 mm x 9.5 mm. This fMRI scan was part of a broader series of imaging sessions.
There are many different ways to analyse the Morris Watermaze (MWM) Performance, but for this analysis we decided to look at the success rate and the time needed to find the submerged Platform.
As we can see in the Graph there is a steady increase in the success
rate in every group. Already on day one the group in the standard cage
seems to have a much worse performance which statistical analysis
confirms. We have a main effect of the environment (F(3,235.22)
= 12.72, p < .001) and a main Effect of the test day
(F(1,229.76) = 57.93, p < .001), but no interaction
between the two (F(3,229.76) = 2.14, p = .097) Taking
a closer look at the Linear-mixed-model revealed, that there also is an
interaction between the day and the enriched Environment group (\(\beta_{EE:day}\) = 0.37, SE = 0.05,
t(235.12) = 7.73, p < .001).
kable(WM_success_rate_LMM_Summary$coefficients
, caption = "Regression Coefficients for the Model Predicting the success rate of the subjects")
| Estimate | Std. Error | df | t value | Pr(>|t|) | |
|---|---|---|---|---|---|
| (Intercept) | 0.3730392 | 0.0482491 | 235.1248 | 7.7315347 | 0.0000000 |
| EnvironmentBC | 0.2436939 | 0.0664587 | 235.3113 | 3.6668446 | 0.0003036 |
| EnvironmentEX | 0.2764978 | 0.0672801 | 235.1248 | 4.1096531 | 0.0000548 |
| EnvironmentEE | 0.3852941 | 0.0630631 | 235.1248 | 6.1096635 | 0.0000000 |
| day | 0.1058824 | 0.0233179 | 229.2443 | 4.5408262 | 0.0000091 |
| EnvironmentBC:day | -0.0145346 | 0.0323021 | 230.2133 | -0.4499601 | 0.6531626 |
| EnvironmentEX:day | -0.0072712 | 0.0325152 | 229.2443 | -0.2236259 | 0.8232476 |
| EnvironmentEE:day | -0.0662990 | 0.0304772 | 229.2443 | -2.1753648 | 0.0306253 |
Another Performance variable is the time the rats needed to reach the platform. The first trial of the first day has been discarded because now learning has yet occurred.
As the Success rate, this graph shows the clear difference between the
standard cage group (SC) and the 3 other groups. This gets confirmed by
the statistical analysis showing a main effect of the group
(F(3,291.11) = 5.33, p = .001) and the day
(F(1,1086.34) = 73.34, p < .001), but again no
interaction between the two (F(3,1086.3) = 1.72, p =
.161).
To get a better understanding of the data we decided to filter out the SC group and set the BC group as the baseline condition, to see if there is a statistical difference between that group and the two more enriched environments. This anlaysis showed, that those two conditions, EE and EX dont differ significantly from the BC group(F(2,214.46) = 2, p = .138).
| Estimate | Std. Error | df | t value | Pr(>|t|) | |
|---|---|---|---|---|---|
| (Intercept) | 39.5750284 | 2.336540 | 215.0285 | 16.9374509 | 0.0000000 |
| EnvironmentEX | 2.1568491 | 3.347197 | 214.5824 | 0.6443747 | 0.5200207 |
| EnvironmentEE | -3.9937405 | 3.125324 | 214.6447 | -1.2778644 | 0.2026775 |
| day | -4.4994287 | 1.042237 | 853.4521 | -4.3170867 | 0.0000177 |
| EnvironmentEX:day | -1.8903967 | 1.483628 | 850.2692 | -1.2741716 | 0.2029508 |
| EnvironmentEE:day | 0.9699779 | 1.386517 | 850.7235 | 0.6995789 | 0.4843815 |
Already, just looking at the pictures reveals a very clear difference in CNPase expression. Not only does the flourescence tagged to the CNPase look much brighter, but the structure itself looks much more.
Picture of the Retrosplenial Cortex of a SC
*picture of the Retrosplenial Cortex of of EE
Analyzing the expression of CNPase paints a clear picture. The ANOVA of the linear mixed model shows, shows us that there is significant difference in the expression of CNPase in the different types of environment in the RSG (F(3,10.99) = 7.56, p = .005) and the RSD(F(3,11.79) = 3.55, p = .048).
CNPase Expression in the granular (RSG) and dysgranular (RSD) region of the Restrosplenial cortex. Values were predicted with a linear mixed model because two different types of Microscopes were used.
This graph times the evolution of FC over time broken down by different groups of enrichment. Samll points represent the individual values for the functional connectivity, lines connect the means of the different groups.
A peculiarity of our data is that for many of the test subjects we have all the measurements, so in the following we will discuss the relationship between performance in the MWM and the functional connectivity between RSC and ACC.
Correlation Between Performance in Mind-Wandering and Functional Connectivity of Anterior Cingulate Cortex (ACC) and Resting-State Connectivity (RSc)
This result was really surprising as it shows, that a higher functional connectivity correlates to a worse performance in the MWM.
The correlation between performance in the water maze and functional connectivity was assessed using Pearson’s product-moment correlation. The analysis revealed a significant positive correlation (r = 0.312, \(\rho\) = 0.312, p = 0.018), indicating that as performance in the water maze improved, there was an associated increase in functional connectivity.
This research underscores the significant impact of enriched environments on cognitive abilities. Rats in enriched environments exhibit substantial and accelerated improvements in spatial learning, challenging conventional assumptions about the role of environmental factors in cognitive performance.
Moreover, the heightened CNPase expression in enriched environments demonstrates links between environmental enrichment and enhanced myelination processes, which probably contribute to cognitive enhancements.
One of the most unexpected findings pertains to the functional connectivity (FC) data between the RSC and ACC. It was surprising to observe that FC appeared to be insensitive to environmental variations. This raises the possibility that the effects of the environment may manifest in a micro structural manner and maybe in ways that our methods are not equipped to detect. Another Factor one should keep in mind is that researching rs-fMRI with animals has its complexities. Rats are usually being partly anesthetized which does influence the functional connectivity (Pan et al. (2015)).